---
title: "A Measure of Closeness of Weak Implication to Strict Implication"
authors:
  - "Masanori B. Okamoto"
doi: ""
url: "https://ijcai.org/proceedings/1979/153"
pdf: "https://ijcai.org/proceedings/1979/0153.pdf"
venue: "Proceedings of the Sixth International Joint Conference on Artificial Intelligence"
year: 1979
pages: ""
track: ""
keywords:
---

# A Measure of Closeness of Weak Implication to Strict Implication

Masanori B. Okamoto

*Proceedings of the Sixth International Joint Conference on Artificial Intelligence*.

## Abstract

The concept of weak implication introduced by R.Boudon is relevant to approximate reasoning which is a subject of the study in AI. The weak implication can be interpreted by the fuzzy material implication which is a binary fuzzy relation. A measure of closeness of weak implication to strict implication is defined as the maximum of distances within the given fuzzy relation,but constructed in the 2x2 contigency table. This measure agrees with the absolute value of Boudon's index f of closeness of weak implication to strict implication under some conditions.